The number on the homepage is a probability, not a prediction. It is a current snapshot of the model's estimate of the likelihood that the Islamic Republic undergoes a full regime change, computed from seven underlying conditions — military, economic, social, political. A high reading means those conditions are stacked against the regime; it does not mean collapse is imminent on any particular date. This is a snapshot of present conditions, not a windowed forecast. Every headline figure on this site is computed end-to-end from the pillar scores using the formulas below. No hand-set numbers, no hidden adjustments: feed the model identical scores and you will get identical outputs.
The model decomposes regime stability into seven structural pillars, each scored 0–100 from open-source evidence, with weights that sum to 1.00. Four pillars measure collapse pressure directly: the more degraded Iran's military, the more fragile its economy, the more mobilized the population, and the more hostile the external environment, the higher the score and the more pressure on the regime. The other three are inverted — they measure defensive strength. A high score on security apparatus cohesion means the IRGC and Basij are still holding the line; a high score on information control means the regime is still setting the narrative; a high score on adaptive capacity means the leadership is still maneuvering effectively. For those three, the formula flips the score (100 − sᵢ) before aggregation. Security cohesion carries the heaviest weight at 25 percent, because in every historical case we calibrated against, the loyalty of the coercive apparatus was the last thing to break.
The headline number is produced in two steps.
Step 1 — Compute the Collapse Pressure Index (CPI). The seven pillar scores are combined into a single weighted sum:
CPI = Σ wᵢ · sᵢ*
For the four direct pillars, sᵢ* = sᵢ. For the three inverted pillars (P2 security cohesion, P6 information control, P7 adaptive capacity), sᵢ* = 100 − sᵢ, so regime strength reduces pressure rather than adding to it. The result is a single number between 0 and 100 that captures how much collapse pressure has built up in the system.
Step 2 — Map CPI to probabilities via two independent logistic functions:
P(RC-1) = 100 / (1 + exp(−0.2 · (CPI − 83)))
P(Any Transition) = 100 / (1 + exp(−0.15 · (CPI − 70)))
RC-1 isolates full regime change. Any Transition is the broader category — managed succession, military takeover, constitutional rupture — and therefore sits above RC-1 at every CPI value. The midpoints (83, 70) and slopes (0.2, 0.15) are calibrated against historical cases of authoritarian failure.
Two implications worth flagging. First, because the curve is steep near the threshold, small movements in pillar scores can shift the headline probability by several points. That is a feature: authoritarian systems fail in non-linear cascades, not smooth declines. Second, the model has no opinion about who or what replaces the current regime — it only measures whether the current arrangement can hold.
The model was calibrated against 11 historical cases of authoritarian regimes under military pressure. Classification accuracy: 10/11 (91%)
• Iraq 1991, Iraq 2003, Libya 2011, Afghanistan 2001, Syria 2024 (collapsed)
• Syria 2011-15, Venezuela 2019 (survived)
• Iran 1979, Egypt 2011, Romania 1989 (transitioned)
Day 93 recalibration (May 31, 2026). A note on integrity. Until this release, the headline RC-1 probability was set manually in the model's data file rather than computed from the pillar scores beneath it. The methodology page described a six-step pipeline — multipliers, a rally dampener, an “RC-1 fraction” — but that pipeline was never actually running. For 73 days, the number you saw was an editorial judgment dressed up as a computation. As of Day 93, the formula described on this page runs end-to-end on every update: CPI is computed from the seven pillar scores, and RC-1 and Any Transition are derived from CPI via the logistic curves. Legacy parameter fields have been retired, not patched. The switch to a live formula produced a small step-change in the headline when it went live; that reflects the gap between human judgment and the formula's output, not a sudden shift in conditions on the ground. We are publishing this caveat openly because the credibility of the model depends on it.